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Control algorithms for programmable logic controllers are still developed based on the experience of those responsible for control in the industry. The IEC-61131-3 standard considers five programming languages: Ladder Diagram, Structured Text, Function Block Diagram, Instruction List, and Sequential Function Diagram, which use different function blocks to develop control algorithms. Within the control algorithms for discrete event systems, there are two types of blocks: those with discrete inputs and outputs, and those with discrete and analog inputs and discrete output. Of the latter, the present research shows the analysis and formal model of the blocks including the problems of accumulation of tokens and the restoration of the coils. This proposal includes logical blocks of timers, counters, positive and negative transition detectors and bistable elements, which, together with the AND, OR, AND-OR, contact lock, auto-loop and Set-Reset logics, can be modeled and analyzed control algorithms with a greater degree of complexity. This guarantees the safety of workers as well as machines.

We consider a multi-adversary version of the supervisory control problem for discrete-event systems (DES), in which an adversary corrupts the observations available to the supervisor. The supervisor’s goal is to enforce a specific language in spite of the opponent’s actions and without knowing which adversary it is playing against. This problem is motivated by applications to computer security in which a cyber defense system must make decisions based on reports from sensors that may have been tampered with by an attacker. We start by showing that the problem has a solution if and only if the desired language is controllable (in the DES classical sense) and observable in a (novel) sense that takes the adversaries into account. For the particular case of attacks that insert symbols into or remove symbols from the sequence of sensor outputs, we show that testing the existence of a supervisor and building the supervisor can be done using tools developed for the classical DES supervisory control problem, by considering a family of automata with modified output maps, but without expanding the size of the state space and without incurring on exponential complexity on the number of attacks considered.

This book provides a comprehensive, systematic treatment of discrete event systems modeling and simulation, covering the five major breakthrough areas in modeling over the past sixty years, and integrating these areas into engineering s most widely used modeling and simulation systems.

Opacity, an important property of the information flow in discrete-event systems (DESs), characterizes whether the secret information in a system is ambiguous to a passive observer (called an intruder). Observation models play a critical role in the analysis of opacity. In this paper, instead of adopting a fully static observation model or a fully dynamic observation model, we use a novel Orwellian-type observation model to study the verification of the current-state opacity (CSO), where the observability of an unobservable event can be re-interpreted once certain/several specific conditions are met. First, a K-delay Orwellian observation mechanism (KOOM) is proposed as a novel Orwellian-type observation mechanism for extending the existing Orwellian projection. The main characteristics of the KOOM are delaying the inevitable information release and narrowing the release range for historical information to protect the secrets in a system to a greater extent than with the existing Orwellian projection. Second, we formulate the definitions of standard and strong CSO under the KOOM. Finally, we address the verification problem for these two types of opacity by constructing two novel information structures called a standard K-delay verifier and a strong K-delay verifier, respectively. An analysis of the computational complexity and illustrative examples are also presented for the proposed results. Overall, the proposed notions of standard and strong CSO under the KOOM capture the security privacy requirements regarding a delayed release in applications, such as intelligent transportation systems, etc.

The development of complex products is challenged by diverse requirements, interdisciplinary coupling, intricate behaviors, and prolonged lifecycles. Traditional document-based systems engineering methods exhibit deficiencies in requirement validation, architectural verification, and cross-disciplinary integration, struggling to support early-stage verification and validation as well as interdisciplinary collaboration. To address these limitations, this paper proposes a scenario-based visual modeling method for the entire lifecycle of complex products, aiming to realize a closed-loop process epitomized by “construction as verification.” This method integrates model-based systems engineering, scenario-driven design, and multi-level visualization techniques to construct a multi-paradigm visual modeling and simulation framework driven by operational scenarios, use-case scenarios, and working-condition scenarios, each serving as the blueprint for constructing the corresponding Operational Concept, Functional/Logical, and Physical Specification Models. Concurrently, a semantic integration mechanism based on hybrid ontologies is introduced, which resolves semantic heterogeneity and facilitates model interoperability among multi-source heterogeneous models through formalized mapping. Furthermore, a simulation engine scheme based on Discrete Event System Specification is proposed to enable continuous verification from conceptual design to solution development. A case study on the braking mechanism of a high-speed train demonstrates that the proposed method can effectively support precise requirement validation, logical architectural verification, and multi-solution trade-off analysis, thereby significantly enhancing early verification capabilities and R&D efficiency.

Discrete Event System Specification (DEVS) is a formalism widely used for modeling and simulating complex systems. The main features of DEVS are defining models in a strict mathematical form and representing systems through hierarchical structures. However, when DEVS models have incorrect connection structures and inappropriate behaviors contrary to design intentions, simulation results can be distorted. This can cause serious problems that may lead to inaccurate decision-making. In this paper, we propose an automated verification framework to improve the accuracy and efficiency of coupled models in the DEVS-Python environment. This framework defines test scripts for coupled models, performs automatic verification before simulation execution, and provides the results to users. Experimental results showed that the proposed framework improved execution time by approximately 30–100 times compared to traditional unit testing methods, although memory and CPU usage increased slightly. Despite this increase in resource usage, the proposed framework provides high efficiency and consistent performance in verifying complex DEVS-coupled models.

A system is said to be critically observable if the operator can always determine whether the current state belongs to a set of critical states. Due to the communication failures, systems may suffer from intermittent loss of observations, which makes the system not critically observable. In this sense, to characterize critical observability in a quantitative way, this paper extends the notion of critical observability to stochastic discrete event systems modeled as partially observable probabilistic finite automata. Two new notions, called step-based almost critical observability and almost critical observability are proposed, which describe a measure of critical observability for a given system against intermittent loss of observations. We introduce a new language operation to obtain a probabilistic finite automaton describing the behavior of the plant system under intermittent loss of observations. Based on this structure, we also present verification methodologies to check the aforementioned two notions and analyze the complexity. Finally, the results are applied to a raw coal processing system, which shows the effectiveness of the proposed methods.

With the development and widespread application of information technology, cybersecurity has become a focal point in all industry sectors. The maritime sector is no exception, with both physical and cyber threats. This survey first highlights, from a system engineering and information technology perspective, the specific architectures of on-vessel and in-port systems, as well as the communication equipment connecting them. Subsequently, cyber attacks in maritime and port domains and their potential consequences are described from various angles. Examples of real cases of cyber attacks are also reported. An overview of current key techniques used in vulnerability analysis, attack detection, and security protection is proposed before discussing cybersecurity issues in the maritime and port sectors from the particular perspective of discrete event systems. Various systems used in maritime and port domains are modeled as automata or Petri nets. Some analysis, detection, and protection approaches are then proposed to illustrate the potential of discrete event systems in this domain.

The increasing penetration of renewable energy presents substantial challenges to frequency stability, particularly in low-inertia microgrids. This study introduces an agent-based microgrid model that integrates generators, loads, an energy storage system (ESS), and renewable sources, mathematically formalized through the discrete-event system specification (DEVS) to ensure both structural clarity and extensibility. To dynamically simulate power system behavior, the model incorporates multiple control strategies—including ESS scheduling, automatic generation control (AGC), predictive AGC, and grid-forming (GFM) inverter control—each posed as an mathematically defined control problem. Simulations on the IEEE 13-bus system demonstrates that the coordinated operation of ESS, GFM, and the proposed strategies markedly enhances frequency stability, reducing frequency peaks by 1.14, 1.14, and 0.72 Hz, and shortening the average recovery time by 9.05, 0.15, and 2.58 min, respectively. Collectively, the model provides a systematic representation of grid behavior and frequency regulation mechanisms under high renewable penetration, and establishes a rigorous mathematical framework for advancing microgrid research.

This paper proposes a DEVS (Discrete Event System Specification) formalism-based approach to analyze Clock Domain Crossing (CDC) issues in digital circuit design. As modern System on Chip (SoC) designs increasingly integrate multiple clock domains, the verification of CDC-related metastability becomes more challenging and costly. While conventional EDA tools offer solutions for CDC analysis, they often involve substantial computational resources and licensing costs. We present a DEVS-based simulation framework that leverages its inherent advantages in time management and modular structuring to model and analyze CDC scenarios. The framework includes a CDC synchronizer model implemented within the HDL partially compatible DEVS environment, enabling precise analysis of metastability violations based on setup time and hold time requirements. Circuit designers or related engineers can potentially solve timing issues such as CDC by incorporating DEVS-based analysis tools into the design pipeline.